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Item Toward a neural aggregated search model for semi-structured documents(CERIST, 2013-07) Bessai, Fatma-ZohraIn this paper, we are interested in content-oriented XML information retrieval. Our goal is to revisit the granularity of the unit to be returned. More precisely, instead of returning the whole document or a list of disjoint elements of a document, as it is usually done in the most XML information retrieval systems, we attempt to build the best elements aggregation (set of non-redundant elements) which is likely to be relevant to a query composed of key words. Our approach is based on Kohonen self-organizing maps. Kohonen self-organizing map allows an automatic classification of XML elements producing density map that form the foundations of aggregated search.Item Possibility and necessity measures for relevance assessment(ACM, 2007-11-09) Bessai, Fatma-Zohra; Boughanem, M.The major question raised in information retrieval on semi-structured documents relates to the manner of effectively handling the structure and the contents of the document for better answering the user's needs. These needs can be formulated by queries composed of only key words or key words and structural constraints. In this paper, we are interested in Information Retrieval in semi-structured document like XML. For these purposes, we present a model for the semi-structured information retrieval, based on the possibilistic networks. The document - elements and elements - terms relations are modelled by measures of possibility and necessity. In this model, the user's query starts a process of propagation to recover documents or portions of documents necessarily or at least possibly relevant. An example of such a research is proposed in order to illustrate the presented approach.